Lived Experiences of Technical-Vocational Students in Learning Science: Challenges and Adaptation
Geraldine Sampayan-Tabat | Susie Daza
Discipline: Education
Abstract:
This qualitative study explored the lived experiences of Grade 11 Technical-Vocational students in learning science at Kapaya National High School, Sultan Kudarat, Philippines. Employing a phenomenological approach, the study examined how environmental and behavioral factors influence students’ engagement with science education. The findings revealed several challenges, including cognitive difficulties in understanding abstract scientific concepts, as well as stress and anxiety linked to academic demands. Despite these barriers, students demonstrated resilience through adaptive coping mechanisms such as time management, peer and teacher support, and self-regulation strategies. Classroom climate and teacher-student interaction emerged as key environmental factors shaping their learning experiences. While students recognized the relevance of science to their vocational aspirations, many expressed a lack of confidence in applying scientific knowledge to their field. These insights emphasize the need for differentiated instructional methods, comprehensive student support systems, and a more inclusive, student-centered learning environment. The study contributes to the limited literature on science education in vocational tracks and underscores the importance of contextually grounded interventions. Its findings aim to inform educational stakeholders in developing responsive policies and practices that enhance both the academic success and personal well-being of Technical-Vocational students.
References:
- Adams, J., & Wang, L. (2022). Science education in vocational schools. Journal of Educational Studies, 45(3), 112–130.
- Aulls, M. W., & Shore, B. M. (2010). Inquiry in education: The conceptual foundations for research as a curricular imperative. Routledge.
- Bandura, A. (2017). Self-efficacy: The exercise of control (Rev. ed.). W. H. Freeman.
- Baniya, R. K., & Shakya, S. R. (2016). Impact of indoor lighting on students’ learning performance in higher education institutes. International Journal of Business and Social Science, 3(24), 84–91.
- Berger, R. (2015). Now I see it, now I don’t: Researcher’s position and reflexivity in qualitative research. Qualitative Research Journal, 15(2), 219–228. https://doi.org/10.1108/QRJ-04-2014-0012
- Bernacki, M. L., Greene, J. A., & Crompton, H. (2020). Self-regulated learning and mobile technology: A systematic review of the literature. Computers & Education, 154, 103896. https://doi.org/10.1016/j.compedu.2020.103896
- Boud, D., Cohen, R., & Sampson, J. (2014). Peer learning in higher education: Learning from and with each other. Routledge.
- Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597. https://doi.org/10.1080/2159676X.2019.1628806
- Broadbent, J., & Poon, W. L. (2015). Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, 1–13. https://doi.org/10.1016/j.iheduc.2015.04.007
- Bybee, R. W. (2014). The BSCS 5E instructional model: Personal reflections and contemporary implications. Science & Children, 51(8), 10–14.
- Cheung, K. L., Li, M. S., & Leung, K. C. (2023). Exploring the key predictors of academic resilience in science. International Journal of Science Education, 45(10), 1–23. https://doi.org/10.1080/09500693.2023.2231117
- Creswell, J. (2021). Phenomenological research in education. Research Methods in Education, 29(2), 200–215. Department of Education. (2020). K-12 science education framework. DepEd Publications.
- Deslauriers, L., McCarty, L. S., Miller, K., Callaghan, K., & Kestin, G. (2019). Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom. Proceedings of the National Academy of Sciences, 116(39), 19251–19257. https://doi.org/10.1073/pnas.1821936116
- Dillenbourg, P. (2016). Collaborative learning: Cognitive and computational approaches. Computers & Education, 99, 1–15. https://doi.org/10.1016/j.compedu.2016.04.002
- Dweck, C. S. (2016). Mindset: The new psychology of success. Penguin Random House.
- Dweck, C. S., & Yeager, D. S. (2019). Mindsets: A view from two eras. Perspectives on Psychological Science, 14(3), 481–496. https://doi.org/10.1177/1745691618804166
- Fia, E. K., Fosu-Ayarkwah, C., & Obuobi-Ayim, E. (2022). Causes, effects and management of science anxiety among senior high school students in Old Tafo Municipality of Ghana. International Journal of Research and Innovation in Social Science, 6(7), 123–130.
- Frykholm, J., & Glasson, G. (2010). Connecting science and mathematics instruction: Pedagogical context knowledge for teachers. School Science and Mathematics, 110(3), 127–134. https://doi.org/10.1111/j.1949-8594.2010.00015.x
- Garcia, M., & Santos, L. (2020). Challenges in science learning among tech-voc students. International Journal of Vocational Studies, 14(1), 50–68.
- Garland, E. L., Farb, N. A., Goldin, P. R., & Fredrickson, B. L. (2015). Mindfulness broadens awareness and builds eudaimonic meaning: A process model of mindful positive emotion regulation. Psychological Inquiry, 26(4), 293–314. https://doi.org/10.1080/1047840X.2015.1064294
- Gillies, R. M. (2016). Cooperative learning: Review of research and practice. Australian Journal of Teacher Education, 41(3), 39–54. https://doi.org/10.14221/ajte.2016v41n3.3
- Holmes, N. G., Kumar, D., & Bonn, D. A. (2017). Toolboxes and handing students a hammer: The effects of cueing and instruction on getting students to think critically. arXiv Preprint, arXiv:1703.07017. https://arxiv.org/abs/1703.07017
- Honicke, T., & Broadbent, J. (2016). The influence of academic self-efficacy on academic performance: A systematic review. Educational Research Review, 17, 63–84. https://doi.org/10.1016/j.edurev.2015.11.002
- Lee, C. K., Tsai, C. C., Chai, C. S., & Koh, J. H. L. (2014). Students’ self-directed learning and critical thinking in a flipped classroom context. Internet and Higher Education, 22, 18–25. https://doi.org/10.1016/j.iheduc.2014.03.002
- Martin, A. J., Mansour, M., Anderson, M., Gibson, R., Liem, G. A. D., & Sudmalis, D. (2019). The role of arts participation in students’ academic and non-academic outcomes: A longitudinal study of school, home, and community factors. Contemporary Educational Psychology, 58, 122–137. https://doi.org/10.1016/j.cedpsych.2019.02.005
- Michael, J. (2021). Where’s the evidence that active learning works? Advances in Physiology Education, 45(1), 81–89. https://doi.org/10.1152/advan.00123.2020
- Mott, M. S., Robinson, D. H., Walden, A., Burnette, J., & Rutherford, A. S. (2012). Illuminating the effects of dynamic lighting on student learning. SAGE Open, 2(2), 2158244012445585. https://doi.org/10.1177/2158244012445585
- National Academies of Sciences, Engineering, and Medicine. (2018). How people learn II: Learners, contexts, and cultures. The National Academies Press. https://doi.org/10.17226/24783
- National Research Council. (2012). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. National Academies Press. https://doi.org/10.17226/13165
- Nasution, S. S., & Rachmat, M. (2021). The effect of time management and academic motivation on students’ learning outcomes. International Journal of Instruction, 14(1), 683–698. https://doi.org/10.29333/iji.2021.14141a
- Orion, N., & Hofstein, A. (2014). Learning in the field: Student experiences in outdoor education. Journal of Science Education and Technology, 23(5), 689–707. https://doi.org/10.1007/s10956-014-9496-3
- Organisation for Economic Co-operation and Development. (2021). Science and industry partnerships in vocational education. OECD Publishing.
- Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 8, 422. https://doi.org/10.3389/fpsyg.2017.00422
- Rahat, E., & Ilhan, T. (2016). Coping styles, social support, relational self-construal, and resilience in predicting students’
- adjustment to university life. Educational Sciences: Theory & Practice, 16(1), 187–208. https://doi.org/10.12738/estp.2016.1.0058
- Roehrig, G. H., Moore, T. J., Wang, H. H., & Park, M. S. (2012). Is adding the “E” enough? Investigating the impact of K-12 engineering standards on the implementation of STEM integration. School Science and Mathematics, 112(1), 31–44.
- Sawyer, R. K. (2014). The Cambridge handbook of the learning sciences (2nd ed.). Cambridge University Press.
- Schunk, D. H., & Zimmerman, B. J. (2012). Motivation and self-regulated learning: Theory, research, and applications. Routledge.